JP2008123409A - Method of supporting increase of efficiency in supply chain - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a method of improving the efficiency of a supply chain by calculating a safety stock to minimize process stock of materials without causing deficiency of the materials even when a production suddenly changes. <P>SOLUTION: When a production changes, an ERP (Enterprise Resource Planning)data conversion program prepares simulation data obtained by classifying materials to be used for a product in each delivery lead time and further classifying the materials by material usage. A supply chain model obtained by modeling a supply chain performs simulation according to the production fluctuation on the basis of the simulation data, calculates a safety stock to minimize process stock of materials as a simulation result without causing deficiency of the materials in production process even when the production suddenly changes, and reflects the safety stock in the supply chain. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to the calculation of the number of appropriate process stocks of materials that does not hinder production even if production fluctuations occur in a supply chain including production processes from material procurement to physical distribution.

  There are multiple business activities such as procurement, production, distribution, and sales of materials from procurement of materials (hereinafter also referred to as parts) to delivery to consumers before the product reaches the consumer. A series of business activities are conducted through The efficiency of such a chain of business activities, the so-called supply chain, has been studied as an important issue.

  When improving the efficiency of such a supply chain with multiple business activities, consideration is given from multiple viewpoints, such as production information such as production volume and delivery date, information on procurement, production, logistics, etc., and information on their bases. It will be necessary. Such a thing is generally called supply chain management (SCM).

  For this reason, in order to improve the efficiency of the supply chain, a method of creating a supply chain model and simulating with a simulator to improve the efficiency of the supply chain has been developed.

  In addition, in the supply chain, if there is a weak part in the chain, such as the flow of information or information, such as an unclear stock quantity, the supply chain may be broken. Therefore, in order to optimize the material flow and information flow of business activities such as material procurement, production, logistics, and sales from material procurement to delivery to consumers, all operations in the supply chain are The flow needs to be captured. Therefore, introduction of an information system package called an ERP (Enterprise Resource Planning) package has been promoted for the core business of a company.

  The ERP package is an integrated business package, which is package software for an enterprise information system that integrates the entire enterprise activities such as sales, production, logistics, and finance. By integrating systems that were built separately for each department so that they can be referenced and used mutually, centralized management of data such as financial accounting and personnel, system upgrades and easy maintenance checks, Real-time reference of work in other departments is also possible.

  In the supply chain, a production plan is prepared according to demand (order), materials are procured from outside or other factories (hereinafter referred to as suppliers), and production activities are performed in the production process. When the material is procured, in addition to the material order confirmation information, in general, the procurement side (ordering side) notifies the supplier of the prospective material ordering information (forecast information) in order to facilitate the procurement. The forecast information is changed to material order confirmation information on a predetermined date. As a result, the supplier can make a future production plan, and it is possible to suppress the occurrence of excess inventory and shortage.

  However, the demand does not always change and production fluctuation may occur when changing from forecast information to material order confirmation information. The production fluctuation may be either a change in production volume, a change in production schedule, or both. For this reason, it is desired to prevent unnecessary stock of materials while preventing production delay due to material shortage even if the production fluctuation occurs.

  On the other hand, the error of the past forecast information, the average value of the error, and the standard deviation of the error are calculated from the past forecast information and the order received corresponding thereto, and the current forecast information is corrected. The calculation of the order quantity is disclosed. (For example, refer to Patent Document 1).

Also, the additional order quantity is calculated by the additional order quantity calculation means that determines the additional order quantity of the resource for the period based on the resource quantity of the resource at the time of use in the additional production. However, it is disclosed to place an order for a member (for example, see Patent Document 2).
JP 2006-39802 A JP 2006-155361 A

  Patent Document 1 corrects the current forecast information and calculates the order quantity, so that the order receiving side can make a highly accurate order prediction, thereby preventing the occurrence of shortage and excessive inventory. It is intended to effectively suppress. However, in the case of a sudden change in order, it is impossible to predict whether or not a shortage will occur, and a shortage may occur.

  Patent Document 2 intends to calculate the additional order quantity by the additional order quantity calculation means, secure the parts while reducing unnecessary inventory as much as possible by placing the parts order, and to cope with fluctuations in the demand of the product. . However, it is only the calculation of the additional order quantity, that is, the additional manufacturable quantity, and when there is a sudden change in the order more than the additional manufacturable quantity, a shortage may occur.

  In general, a product is composed of a plurality of materials. For example, in a copying machine, a main material is composed of several hundred points. In general, the materials are shared with other products for ordering, managing, and reducing costs at the product design stage, but there are materials dedicated to products. Also, even for the same product, the product specifications are often different for each destination (shipping destination), for example, for Japan, the United States, Europe, Asia, etc. For example, there are specifications specific to the destination, such as power supply specifications, languages, and safety standards, and there are materials that differ for each destination.

  Due to the above, within the product, common materials between products that are common to other products, common materials within the same product regardless of destination, and dedicated materials within the same product that differ from destination to destination within the same product Are mixed.

  Here, the material use category is, for example, a material used for a product for a certain destination when the specifications differ depending on the destination (shipment destination) of the product and there are different materials to be used. Are divided into common materials for products, common materials for products, and dedicated materials for in-product use.

  Further, the delivery lead time of the material is generally not uniform but varies depending on the material, and the same or different items are mixed in one product.

  Here, the delivery lead time is a period from when the procurement side places an order to delivery by the supplier, for example, the number of days.

  However, in the calculation of the number of safety stocks when production fluctuations have occurred, conventionally, the number of safety stocks has been calculated by collectively simulating materials using a supply chain model. As a result, excessive inventory or shortage may occur.

  The present invention has been made in view of the above situation, and it is possible to calculate the supply of safety stock by calculating the number of safety stocks in which the process inventory of the material is minimal and no material shortage occurs in the process even if sudden production fluctuation occurs. The purpose is to provide an efficiency support method for improving the efficiency of the chain.

The above object is achieved by the following method.
1. Material ordering information shifts from prospective material ordering forecast information (forecast information) to material order confirmation information, and includes production plans that may cause production fluctuations. In the supply chain efficiency support method to set up a supply chain model that models the supply chain of material logistics leading to the first), reproduce it on a computer and simulate it, and improve the efficiency of the supply chain,
Setting a supply chain model that models the supply chain on a computer;
When a production fluctuation occurs in the supply chain, a variable production plan and a material usage amount based on the variable production plan are drafted, and the variable production plan and the material usage amount are input to a storage unit as production fluctuation information; ,
Retrieving the production variation information from the storage means;
Extract the product information and production information from an ERP (Enterprise Resource Planning) package that stores product information and production information, classify materials by delivery lead time, and create simulation data that classifies by use category Creating the simulation data with ERP data conversion means;
Based on the production variation information, the product information, the production information, and the simulation data in the supply chain model, a simulation corresponding to the production variation is performed by a simulator, and the production process inventory of the material at the time of production variation is minimized and Calculating the number of safety stocks that will not cause a shortage,
A supply chain efficiency support method characterized by comprising:
2. The classification for each use category includes common materials between products that are common to other products, common materials within the same product regardless of the destination within the same product, and different internal destinations within the same product for each destination. 2. The supply chain efficiency support method according to 1, wherein the supply chain efficiency support method is performed in a dedicated material classification.
3. 3. The supply chain efficiency support method according to 1 or 2, wherein the production fluctuation pattern is a pattern in which one or more of a production amount and a production schedule fluctuate.
4). 4. The supply chain efficiency support method according to any one of claims 1 to 3, wherein the product information includes a material used for the product, a quantity of the material, a process chart of the product, and data of the configuration.
5. 5. The production information according to any one of 1 to 4, wherein the production information includes production plan information of product production volume and delivery date, material inventory information, ordering information, delivery date information, price information, and product inventory information. Supply chain efficiency support method.
6). In the simulation, the supply chain base information stored in the storage means, information related to the communication environment status, communication environment information, and distribution information related to the distribution status are extracted and added to perform the simulation. 6. The supply chain efficiency support method according to any one of 1 to 5.

  According to the above method, it is possible to calculate the number of safety stocks in which the production process inventory of the material is the minimum and no material shortage occurs in the production process even if a sudden production fluctuation occurs. This makes it possible to effectively suppress material shortages and excess inventory when production fluctuations occur in the supply chain.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings, but the present invention is not limited thereto.

  FIG. 3 is a table showing an example of transition of forecast information (hereinafter also referred to as forecast) and material order confirmation information (hereinafter also referred to as order confirmation). FIG. 3 shows an example in which the order interval, the forecast transmission interval, and the delivery lead time are set to one week. These intervals are appropriately set depending on the types of products and materials, and are, for example, two weeks or one month. The intervals may be different. In FIG. 3, the order confirmation is denoted as PO and the forecast as FC.

  In accordance with the production plan drafted by the initial order, PO1 of the final order is placed in the planned ordering week, and the forecast FC1 is transmitted. PO1 is delivered in 2 weeks. In 2 weeks, FC2 is changed to PO2 and an order is placed, and a forecast FC2 is transmitted. PO2 is delivered in 3 weeks. The same goes for the following. FIG. 3 shows an example in which delivery is completed in nine weeks.

  In the example of FIG. 3, the ordering is performed by creating a material requirement plan by MRP (Material Requirements Planning) or the like based on the production plan every week.

  FIG. 6 is an example in which the materials of the product A whose destinations are A1, A2, A3, and A4 are classified by use classification. The material of the product A is classified into a common material between products (class 1), an in-product common material (class 2), and destination materials A1, A2, A3, and A4 dedicated materials (class 3). The inter-product common material is common to other products, in FIG. 6, the product B, and the in-product common material is common to the destinations A1, A2, A3, and A4. This classification is appropriately set according to product specifications, product configuration, etc., and is not limited to this embodiment.

  Figure 1 shows material logistics from material procurement through production processes to customers (product shipping destinations), including production plans where the ordering information of materials shifts from forecast to finalization and production fluctuations may occur. It is a block diagram which shows one Embodiment of the efficiency improvement support method of the supply chain which aims at efficiency of a supply chain.

  In FIG. 1, a database 1 is a storage means for storing the various data and information described above, and data and information of the ERP package 2 are also required via the relay program 4 and the ERP data conversion program 10 which is an ERP data conversion means. It is taken in according to. In addition, simulation data created by an ERP data conversion program 10 described later is also captured. Note that the data of the ERP package 2 and the data and information that are not used in the ERP data conversion program 10 among the information may be taken directly into the database 1 via the relay program 4 instead of the ERP data conversion program 10.

  The ERP package 2 is an integrated business package, has an integrated database, and stores product information, production plan information, and production information. The product information is based on the materials used for the product and the quantity of the materials, the process schedule and data of the product, the production plan information is based on the product production volume, the production lead time, the delivery date, etc. The production information is the material delivery route , Delivery lead time, inventory, ordering, delivery date, price information, product inventory information, etc. In the present embodiment, SAP (R / 3) (registered trademark) manufactured by SAP is preferably used as the ERP package 2.

  Hereinafter, the ERP package 2 is also referred to as SAP (R / 3) (registered trademark).

  When production fluctuation occurs in the initial production plan, the production plan creation section 3 creates a fluctuation production plan, and the relay program 4 and the ERP data conversion program 10 use the fluctuation production plan and the material usage based on the fluctuation production plan as production fluctuation information. Is input to the database 1 via. Note that the data may be directly input to the database 1 via the relay program 4 instead of the ERP data conversion program 10.

  The production fluctuation pattern is a pattern in which one or more of the production volume and production schedule fluctuate. For example, when the production amount fluctuates, there are a pattern in which the production amount in a certain production period is fluctuated, a pattern in which the production period is fluctuated without changing the production amount, or a mixed pattern of two patterns.

  The ERP data conversion program 10 classifies materials for each delivery lead time based on the product information and production information data, and further creates simulation data classified for each use category. The simulation data is input to the database 1. By using the ERP data conversion program 10 and linking with the ERP package 2, the material classification can be easily performed, and the classification can always be performed with the latest data. For example, even when the design change occurs and the data of the ERP package 2 is corrected, the ERP data conversion program 10 can always create simulation data based on the latest data of the ERP package 2.

  The supply chain model is set as a supply chain model according to the material classification based on the simulation data on the computer by the model creation unit 5 based on the information such as the supply chain configuration stored in the database 1. The

  The supply chain model simulates an actual supply chain on a computer as a virtual supply chain. The actual flow of goods in the supply chain, each operation, etc. can be simulated on a computer.

  The simulation condition setting unit 6 sets simulation conditions such as a simulation period, for example, a period after the occurrence of production fluctuation, a parameter such as an initial inventory setting, a production amount setting for a unit period, and the like. .

  In the simulation unit 7, a simulation is performed with the set supply chain model based on the production variation information, the product information, the production information, the simulation data, and the simulation conditions. Based on the simulation, the number of safety stocks with a minimum production process stock at the time of production fluctuation and no shortage is calculated.

  The simulation data is always created by the ERP data conversion program 10 based on the latest data of the ERP package 2 as described above. For this reason, simulation close to an actual system and with high accuracy becomes possible.

  In the simulation, it is preferable to perform a simulation by taking out from the database 1 information on the bases constituting the supply chain, information on the communication environment, communication environment information, and distribution information on the state of distribution. This makes it possible to perform a simulation that is closer to the actual system and with high accuracy.

  The result evaluation unit 8 evaluates and examines the result of the simulation (the number of safety stocks), and if it is necessary to change the conditions for simulation, the simulation condition setting unit 6 can set the conditions again and perform the simulation. it can. Thereby, the range of evaluation can be expanded.

  Information on the simulation result is stored as feedback data in the database 1 and further transferred to the ERP package 2 via the ERP data conversion program 10 and the relay program 4 to be reflected. Alternatively, the data may be transferred from the database 1 directly to the ERP package 2 via the relay program 4 without going through the ERP data conversion program 10.

  The simulation result transferred to the ERP package 2 is taken into the supply chain 9 and reflected in the material requirement plan creation, order confirmation, and forecast of actual materials.

  FIG. 2 shows an example of a flowchart for improving the efficiency of the supply chain using the supply chain efficiency support method shown in FIG. It is assumed that necessary data and information are captured from the ERP package 2 in the database 1.

  In step S101, based on the product information and production information data of the ERP package 2, the ERP data conversion program 10 classifies the materials for each delivery lead time and further creates simulation data classified for each usage category. .

  In step S102, the model creation unit 5 creates a supply chain model that models the supply chain on the computer based on information such as the supply chain configuration stored in the database 1. The supply chain model is created as a classified supply chain model based on the simulation data created in step S101.

  In step S103, the production plan creation unit 3 drafts a variable production plan based on the production fluctuation information, and sets a material usage amount associated therewith. The fluctuating production plan and the material usage are input to the database 1 as production fluctuation information.

  In step S104, the simulation condition setting unit 6 sets simulation conditions by the person in charge. The setting of the simulation conditions includes a simulation period, an initial inventory setting, a parameter setting such as a production amount setting for a unit period, and the like.

  In step S105, the simulation unit 7 performs a simulation using the supply chain model, and calculates a safety stock number that minimizes the process stock in the case of the production fluctuation and does not cause a shortage as a simulation result.

  In step S106, the result evaluation unit 8 evaluates and evaluates the simulation result (the number of safety stocks). Further, when it is necessary to change the conditions for the simulation (step S105; NO), the conditions are set again in step S103 and the simulation is performed. If re-simulation is not required (step S105; YES), the simulation result is stored in the database 1 in step S106.

  In step 108, the simulation result is transferred from the database 1 to the ERP package 2 and reflected in the data and information of the ERP package 2.

  As a result of the above, it becomes possible to capture the results of the simulation when creating the material requirement plan by MRP or the like in the supply chain 9, and the delivery date change instruction, delivery quantity change instruction, etc. are reflected in the material requirement plan creation in real time. It becomes possible to make it. This makes it possible to effectively suppress material shortages and excess inventory when production fluctuations occur in the supply chain 9.

In addition, the supplier can obtain information on the simulation results from the ERP package 2, and can make future production plans, suppressing the occurrence of excess inventory and shortage even if sudden production fluctuations occur. It becomes possible to do.
<Example>
Next, when production fluctuations occur according to the present invention, the ERP data conversion program 10 classifies the materials used for the product by delivery lead time, and further creates simulation data classified by use category. An example of using a supply chain efficiency support method that performs a simulation with a supply chain model and calculates the number of safety stocks of a material that has a minimum production process stock at the time of production fluctuation and does not cause a shortage will be described.

  The following is an example in the case where production fluctuation occurs in the model A1 which is the destination A1 of the product A whose destinations are A1, A2, A3 and A4 shown in FIG.

  The material of product A is classified by delivery lead time. The materials classified according to the delivery lead time are further divided into common materials for each product category (class 1), common materials for products (class 2), and dedicated materials for destinations A1, A2, A3, A4 ( Class 3).

  FIG. 4 shows a group of class A1, a group of parts a1 with a delivery lead time of 2 weeks, a group a2 of class 2, a group a3 of class 3, and a group of parts with a delivery lead time of 4 weeks. It is a figure which shows transition of the order and forecast of b1, b2, b3. If the delivery lead time is the same, the transition shows the same transition regardless of the classification for each usage category. Therefore, the groups a1 to 3 are referred to as a group a, and the groups b1 to b are referred to as a group b.

  In FIG. 4, the order confirmation of the group a is indicated by PO (n), the forecast is indicated by FC (n), the order confirmation of the group b is indicated by POb (n), and the forecast is indicated by FCb (n).

  In accordance with the production plan drafted by the initial order, the group a is ordered PO1 at the beginning of the week in order week 1 and forward FC3 is transmitted. PO1 is delivered at the beginning of the third week. Similarly, at order week 2, PO2 is ordered and FC4 is transmitted. PO2 is delivered at the beginning of 4 weeks. In order week 3, FC3 is changed to PO3 and ordered, and a forward FC5 is transmitted. PO3 will be delivered at the beginning of week 5. The same goes for the following.

  Orders and forecasts for group b are also made in a form according to group a.

  The ordering is performed by creating a material requirement plan by MRP (Material Requirements Planning) or the like based on the production plan every predetermined period. In the example of FIG. 4, the order is made every week, and the order for 4 weeks is made in the material requirement plan of MRP number 4 made in 3 weeks. Further, the period shown in FIG. 4 may be regarded as a certain period during which production is continued.

  When fluctuations in production volume occur in the ordering and forecasting transitions in the 5th week (arrow d in the figure), a variable production plan is drawn up, and the variable production plan and the material usage based on the variable production plan change the production. Created as information.

  Based on the production variation information, the product information, the production information, the simulation data, and the simulation conditions, the supply chain model is used to classify materials for each delivery lead time, and further class for each use category. A divided simulation is performed to calculate the number of safety stocks that have a minimum production process inventory at the time of production fluctuation and that do not cause a shortage.

  The calculation is performed in consideration of the number of safety stocks of other products as materials common to other products at the level of the material use class 1, that is, common materials between products. At the class 2 level, a calculation is performed in consideration of the number of safety stocks for other destinations of materials common to destinations within the same product, that is, common materials within products. At the class 3 level, a material dedicated to the model A1, that is, a dedicated material for in-product finishing is calculated.

  The safety stock quantity is reflected in group b in the material requirement plan with MRP number 6 for 5 weeks. Based on the material requirement plan with the MRP number 6, POb 6 is confirmed and ordered in group b and delivered at the beginning of the 10th week.

  Here, the production based on the variable production plan is started after the POb 6 of the group b, which is generally a group having a long delivery lead time, is delivered in this embodiment. For this reason, the safety stock quantity at the time of production fluctuation calculated by the above simulation is the stock quantity applied at the beginning of the 10th week.

  For this reason, for the group a, the safety stock number may be reflected in FC8. That is, the safety stock quantity is reflected in the group a in the material requirement plan with MRP number 8 for 7 weeks. Based on the material requirement plan with MRP number 8, PO8 is confirmed and ordered in group a and delivered at the beginning of the 10th week.

  In this way, when simulating the supply chain model and calculating the safety stock number of materials that have the smallest production process inventory at the time of production fluctuation and do not cause missing items, the materials are classified by delivery lead time, Furthermore, by classifying for each usage category and performing a simulation, an appropriate number of safety stocks can be calculated. Thereby, it is possible to place an order at an appropriate time according to an appropriate material according to the material use classification and a delivery lead time. This makes it possible to effectively suppress material shortages and excess inventory when production fluctuations occur in the supply chain 9.

  If the production fluctuation is a decrease in production volume, there will be no shortage. Similarly to the above, the material requirement plan based on the safety stock number at the time of production fluctuation calculated by simulation is reflected in PO8 and POb6, and the order quantity is adjusted.

  Further, the simulation can be classified for each use category, and can be performed for each part in the class. However, in a product having several hundred main parts such as a copying machine, it is very complicated to perform simulation for each part. In addition, there are many parts with the same delivery lead time, and the same thing is repeated, and costs and time are consumed.

For this reason, it is effective to perform the simulation by classifying for each delivery lead time and classifying for each usage classification as in the present invention.
<Comparative example>
In the following, a case where the individual delivery lead time of the material is not referred to when the production fluctuation occurs and the case where the material is not classified for each use classification will be described as a comparative example with reference to FIGS. 4 and 5. In the following description, except the description, it is the same as the said Example.
(1)
This is an example of calculating the number of safety stocks by referring to the supply chain model without referring to the individual delivery lead times of the materials and without classifying the materials for each use category.

  As in the above <Example>, based on the production variation information, the product information, the production information, and the simulation conditions, simulation is performed with the set supply chain model, and the production process inventory at the time of production variation is minimized. And the number of safety stocks that do not cause missing items is calculated. The safety stock quantity is reflected in the material requirement plan with MRP number 6 for 5 weeks. Based on the material requirement plan with the MRP number 6, PO6 is confirmed and ordered in group a. In group b, POb6 is confirmed and an order is placed.

  However, group a PO6 is delivered at the beginning of week 8 and group b POb6 is delivered at the beginning of week 10. Since the production is generally started after the POb 6 of the group b is delivered, the increase due to the production fluctuation of the PO 6 of the group a becomes an unnecessary stock, that is, an excess stock during the period S in FIG.

  Further, since no classification is performed for each material usage category, all materials are simulated in the maximum product configuration, that is, in class 1. For this reason, all the parts of the product A, which are linked to the so-called product A, are subjected to the simulation, and the production-specific parts of the models A2 to 4 are also safe due to the production fluctuations despite the production fluctuations of the model A1. The inventory quantity is calculated, reflected in the material requirements plan, and ordered. However, the order for the variation of the parts dedicated to the destinations of the models A2 to A4 is an unnecessary order, which is also excessive stock.

When the production fluctuation is a decrease in the production quantity, the material requirement plan based on the number of safety stocks at the production fluctuation calculated by the simulation is reflected in PO6 and POb6, and the order quantity is adjusted. For this reason, the order quantity is adjusted at PO6 corresponding to the production prior to the production based on the variable production plan, and there is a possibility that a part out of the group a may be out of stock.
(2)
In this example, classification is performed for each material usage category, but the number of safety stocks is calculated by performing a simulation with a supply chain model without referring to the individual delivery lead times of the materials.

In the above <Comparative Example> (1), the classification is made for each material use category, and the dedicated parts for destinations of models A2-4 are not subject to the calculation of the safety stock number due to production fluctuations. No order is placed for the variation of destination-specific parts for models A2-4. However, since the delivery lead time is not referred to, unnecessary inventory during the period S in FIG. 5, that is, excess inventory occurs, as described in (1) above.
(3)
This is an example of calculating the number of safety stock by performing a simulation with a supply chain model with reference to each delivery lead time of the material without classifying each material usage category.

  In the above <Example>, the classification for each material usage category is not performed, and the classification for each material usage category is not performed. A simulation is performed for each delivery lead time.

  For this reason, all the parts of the product A, which are linked to the so-called product A, are subjected to the simulation, and the production-specific parts of the models A2 to 4 are also safe due to the production fluctuations despite the production fluctuations of the model A1. The inventory quantity is calculated, reflected in the material requirements plan, and ordered. However, the order for the variation of the destination-specific parts for the models A2 to A4 is an unnecessary order and is excessively in stock.

It is a block diagram which shows one Embodiment of the efficiency improvement support method of the supply chain which concerns on this invention. An example of the flowchart which aims at the efficiency improvement of the supply chain which concerns on this invention is shown. It is a figure which shows transition of forecast information and material order confirmation information. It is a figure which shows the transition in the case of classifying for every delivery lead time of materials, and performing a simulation with a supply chain model. It is a figure which shows transition in the case of simulating a material in a supply chain model collectively. It is the figure which classified the material of product A according to use classification.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Database 2 ERP package 3 Production plan creation part 4 Relay program 5 Model creation part 6 Simulation condition setting part 7 Simulation part 8 Result evaluation part 9 Supply chain 10 ERP data conversion program

Claims (6)

Material ordering information shifts from prospective material ordering forecast information (forecast information) to material order confirmation information, and includes production plans that may cause production fluctuations. In the supply chain efficiency support method to set up a supply chain model that models the supply chain of material logistics leading to the first), reproduce it on a computer and simulate it, and improve the efficiency of the supply chain,
Setting a supply chain model that models the supply chain on a computer;
When a production fluctuation occurs in the supply chain, a variable production plan and a material usage amount based on the variable production plan are drafted, and the variable production plan and the material usage amount are input to a storage unit as production fluctuation information; ,
Retrieving the production variation information from the storage means;
Extract the product information and production information from an ERP (Enterprise Resource Planning) package that stores product information and production information, classify materials by delivery lead time, and create simulation data that classifies by use category Creating the simulation data with ERP data conversion means;
Based on the production variation information, the product information, the production information, and the simulation data in the supply chain model, a simulation corresponding to the production variation is performed by a simulator, and the production process inventory of the material at the time of production variation is minimized and Calculating the number of safety stocks that will not cause a shortage,
A supply chain efficiency support method characterized by comprising: The classification for each of the above usage categories is common materials between products that are common to other products, common materials within the same product regardless of the destination within the same product, and different internal destinations within the same product for each destination. The supply chain efficiency support method according to claim 1, wherein the supply chain efficiency support method is performed in a dedicated material classification. 3. The supply chain efficiency support method according to claim 1, wherein the production fluctuation pattern is a pattern in which one or more of a production amount and a production schedule fluctuate. 4. The supply chain efficiency support according to claim 1, wherein the product information includes material used for the product, the quantity of the material, a process schedule of the product, and data of the configuration. 5. Method. 5. The production information according to claim 1, wherein the production information includes production plan information of product production amount and delivery date, material inventory information, ordering information, delivery date information, price information, and product inventory information. Supply chain efficiency support method described in 1. In the simulation, the supply chain base information stored in the storage means, information related to the communication environment status, communication environment information, and distribution information related to the distribution status are extracted and added to perform the simulation. The supply chain efficiency support method according to any one of claims 1 to 5.

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